Interesting papers:
First, we will plot all the trials and see if there are group effects.
#load omnibus dataframe
omnibus_df <- read_delim("data/omnibus/omnibus_throws.csv",
delim = ",",
col_types = cols(.default = col_double(),
type = col_factor(),
ppid = col_factor(),
experiment = col_factor(),
hand = col_factor(),
per_block_list_camera_tilt = col_factor(),
per_block_list_surface_tilt = col_factor(),
per_block_targetListToUse = col_factor(),
per_block_surface_materials = col_factor()))
Warning: One or more parsing issues, call `problems()` on your data frame for details, e.g.:
dat <- vroom(...)
problems(dat)
all_throw_summary <- omnibus_df %>%
group_by(experiment, trial_num) %>%
summarise(mean = mean(error_size, na.rm = TRUE),
sd = sd(error_size, na.rm = TRUE),
ci = vector_confint(error_size),
n = n(), .groups = "drop")
p <- omnibus_df %>%
ggplot(aes(x = trial_num, y = error_size)) +
# geom_point(alpha = 0.04, aes(colour = experiment)) +
geom_ribbon(data = all_throw_summary,
aes(y = mean, ymin = mean-ci,
ymax = mean+ci, fill = experiment),
alpha = 0.3) +
geom_line(data = all_throw_summary,
aes(y = mean, colour = experiment)) +
theme_minimal() +
# scale_x_continuous(limits = c(205, 374)) +
NULL
ggplotly(p)
# save plot
# ggsave(p, height = 9, width = 16, device = "svg", filename = "data/figs/all_throws.svg")
ggplotly(plot_success_manifold_no_tilt())
ggplotly(plot_success_manifold_tilt())